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Stacking sequence optimisation of an aircraft wing skin

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2023年第2期66卷 31-31页

作者： Ntourmas, Georgios Glock, Florian Deinert, Sebastian Daoud, Fernass Schuhmacher, Gerd Chronopoulos, Dimitrios Ozcan, Ender Ninic, Jelena Univ Nottingham Inst Aerosp Technol & Composites Res Grp Nottingham NG7 2RD England Airbus Def & Space GmbH Stress Methods & Optimisat D-85077 Manching Germany Tech Univ Munich Dept Aerosp & Geodesy D-85521 Munich Germany Katholieke Univ Leuven Dept Mech Engn & Mecha tro N Syst Dynam LMSD B-9000 Ghent Belgium Univ Nottingham Computat Optimisat & Learning Lab Nottingham NG7 2RD England Univ Birmingham Sch Engn Birmingham B15 2TT England

This paper demonstrates a stacking sequence optimisation process of a composite aircraft wing skin. A two-stage approach is employed to satisfy all sizing requirements of this industrial sized, medium altitude, long endurance drone. In the first stage of the optimisation, generic stacks are used to describe the thickness and stiffness properties of the structure while considering both structural requirements and discrete guidelines such as blending. In the second stage of the optimisation, mathematical programming is used to solve a mixed integer Linear programming formulation of the stacking sequence optimisation. The proposed approach is suitable for real-world thick structures comprised of multiple patches. Different thickness discretisation strategies are examined for the retrieval of the discrete stacking sequences, with each one having a different influence on the satisfaction of all structural constraints across the various sub-components of the wing. The weight penalty introduced between the continuous and final discrete design of the proposed approach is negligible.

关键词： Stacking sequence optimisation Detailed sizing Generic stacks mixed integer programming

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Towards resilient and smart urban road networks: Connectivity restoration via community structure

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SUSTAINABLE CITIES AND SOCIETY 2021年 75卷 103344-103344页

作者： Luo, Zhongwei Yang, Bo Wuhan Univ Technol Sch Automat Wuhan 430070 Peoples R China

In the time of global warming, smart and resilient cities need to have the ability to give quick responses to today's frequent natural disasters. Building a resilient urban transportation system that can timely recover the accessibility of the rescue facilities is vital to the survival chances of citizens. From the perspective of selectively road restoration, we proposed a mixed integer programming model that is based on community hierarchy to provide quick disaster response for damaged urban road networks. This model can efficiently find roads that should give repairing priority to maximize the connectivity in a limited repairing scale. Network community structure has been innovatively introduced into our model, which can remarkably simplify the searching process by extracting critical connectivity information. The model has been tested on square-shaped road networks and Istanbul road networks. The results show that our community structure model gives superior solutions in significantly reduced computational time, and is practical in solving complex real-world large-scale connectivity repairing problems. These findings provide new insights into the understanding of the important role played by mesoscopic topological knowledge of road networks when seeking strategies and solutions for connectivity emergency restoration, which is significant for the development of resilient and sustainable cities.

关键词： Disaster response Road networks Community structure Connectivity restoration mixed integer programming

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Moving time domain blending operational strategy for alumina production by mixed integer optimization

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COMPUTERS & CHEMICAL ENGINEERING 2022年 166卷

作者： Yin, Yanyan Kong, Lingshuang Yang, Chunhua Gui, Weihua Teo, Kok Lay Curtin Univ Sch Elect Engn Comp & Math Sci Perth WA 6102 Australia Hunan Univ Technol Coll Elect & Informat Engn Taishan Rd Tianyuan Zhuzhou Peoples R China Cent South Univ Sch Automat South Lushan Rd Changsha Peoples R China Sunway Univ Sch Math Sci Subang Jaya Malaysia

The preparation of quality raw slurry is a complicated and crucial process in alumina production which determines the cost and efficiency of the entire production. In the mixing unit, some tanks with fully filled raw slurry are available to be selected in each round, and the components in these selected tanks are required to be mixed, meanwhile some ratios of chemical compositions in the final mixture must be strictly within the required level. This is the production procedure of quality raw slurry. To improve production efficiency and reduce operation time lags, this selection and proportioning problem is formulated as a mixed integer programming problem. An optimization algorithm developed based on the moving time domain is applied to find the optimal selection and the optimal mixing proportioning strategy such that the productivity of the quality raw slurry is maximized. Practical on-site comparison experiments are carried out using the proposed method and the method based on the experience of the operator. The results obtained show that the proposed approach is effective and has advantage in the preparation of quality raw slurry with high efficiency and maximal productivity.

关键词： Alumina production Blending process mixed integer programming Moving time domain Proportioning of raw slurry

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The impact of inventory management on economic and environmental sustainability in the apple industry

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2019年 163卷 104848-000页

作者： Paam, P. Berretta, R. Heydar, M. Garcia-Flores, R. Univ Newcastle Sch Elect Engn & Comp Newcastle NSW Australia CSIRO Data61 Clayton Vic Australia

This paper investigates the impact of inventory management optimization on fruit loss, and inventory and processing costs in apple supply chains. It proposes new inventory policies regarding the configuration of high-tech storage rooms, where apples are stored to meet the annual demand. Each configuration gives rise to a different set of storage room, which will preserve the apples for a specified period of time. To quantify the impact of these policies, we apply a mathematical programming model to the Australian apple industry and analyze the results for two different configurations of storage rooms: (1) a fixed number of each type of storage room and (2) a flexible arrangement in which different numbers of storage rooms of each type are active during different time periods. The comparative effectiveness of the two scenarios is investigated through a case study. The flexible configuration is found to be superior as it reduces fruit loss and total storage and processing costs by 7.7% and 1.5%, respectively, over the fixed configuration. Finally, a comprehensive sensitivity analysis of some of the parameters of the model is performed. This allows the provision of valuable insights and recommendations which empower apple industry stakeholders to improve their inventory performance.

关键词： Food supply chain Inventory management Apple supply chain Food loss mixed integer programming Sustainability

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A topology and sizing optimisation method for lightweight sandwich structures subject to dynamic and static constraints

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COMPOSITE STRUCTURES 2024年 348卷

作者： Larsson, Johan Goransson, Peter Wennhage, Per KTH Royal Inst Technol Dept Engn Mech Tekn Ringen 8 S-10044 Stockholm Sweden Ctr ECO2 Vehicle Design Stockholm Sweden

A static-dynamic topology-sizing optimisation method is presented. The solution is based on a sequential mixed- integer Linear programming solution and aims to minimise the mass of a structure subjected to concurrent constraints on static and dynamic response. It is shown that the classical problem of the dynamics of lightweight sandwich structures may be mitigated through core topology and face sheet thickness combinations, retaining the static load carrying capacity while presenting stringent dynamic properties at a low mass penalty. A numerical example, in the form of a load carrying sandwich beam which is excited at different frequencies, is used to demonstrate the method.

关键词： Topology optimisation Multifunctional structures Sandwich structures TOBS mixed integer programming

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PERIODIC DUE DATE ASSIGNMENT WITH FAMILY SETUPS

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2019年第6期26卷 945-961页

作者： Sertdemir, Sevilay Unal, Ali Tamer Duzgit, Zehra Bogazici Univ Dept Ind Engn Istanbul Turkey Istanbul Bilgi Univ Dept Ind Engn Istanbul Turkey

In this study we consider a single machine due date assignment problem involving dynamic job arrivals and family setups. The due date quotation process is based on periodically generating schedules of new and old jobs. We want to keep the tardiness of old jobs below an allowable threshold while minimizing total completion time of new arriving jobs. We propose a mixed integer linear programming formulation to solve the scheduling problem. We also present a function to quote due dates for new jobs. An experimental analysis is conducted to analyze the proposed due date quotation process under various shop and solution procedure parameters. Three performance measures are considered: average quoted lead time, average tardiness, number of setups perfouned. The first significant outcome of our analysis is that existence of family setups plays a crucial role;the second significant observation is that batching plays a double-edged sword role in due date management.

关键词： scheduling due date assignment lead time quotation family setup mixed integer programming

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A goal-programming based optimal port docking scheme under COVID-19

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OCEAN & COASTAL MANAGEMENT 2022年第0期225卷 106222页

作者： Muren Meng, Weiyue Li, Guorong Hua, Lianlian Jilin Univ Finance & Econ Sch Stat Changchun 130117 Peoples R China Inner Mongolia Univ Technol Sch Econ & Management Hohhot 010021 Peoples R China Inner Mongolia Univ Technol Management Coll Sch Econ Hohhot 010051 Inner Mongolia Peoples R China Jilin Univ Finance & Econ Sch Stat Changchun 130117 Jilin Peoples R China

The Covid-19 epidemic, has caused a large-scale congestion in many ports around the world. This increases the cost of port docking, as well as delays the loading and unloading of goods, which affects the price and timely supply of many products. Although scholars have carried out in-depth discussion and analysis on the port congestion problem from different perspectives, there is still no appropriate model and algorithm for the largescale comprehensive port docking problem. This paper presents a new mixed integer programming model for optimal docking of ships in ports that is comprehensive enough to include four essential objectives. It discusses the generalization and application of the model from the perspectives of the shortest overall waiting time of ships, the balance of tasks at each berth, completion of all docking tasks as soon as possible and meeting the expected berthing time of ships. We demonstrate the results of our models using relevant examples and show that our model can obtain the optimal docking scheme based on different perspectives and relevant objectives. We also show that the scale of the exact solution can reach tens of thousands of decision variables and more than a million constraints. This fully reflects the possibility that the model can be put into use in any real life scenario. This model can not only effectively improve the docking efficiency of the port, but is also suitable for the complex queuing problem of multi window and the same type of service.

关键词： Port docking Berth Goal programming mixed integer programming Time window

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Resource planning for aircraft refueling in airport parking area

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Transportation Research Procedia 2019年 37卷 250-257页

作者： Pasquale Carotenuto Stefano Giordani Alessio Salvatore Andrea Biasini Consiglio Nazionale delle Ricerche Istituto per le Applicazioni del Calcolo “M. Picone” via dei Taurini 19 Rome 00185 Italy Università di Roma Tor Vergata Dipartimento Ingegneria dell’Impresa via del Politecnico 1 Rome 00133 Italy

This paper studies a scheduling problem application for the optimization of the employees used in aircrafts’ refueling in a medium size airport. The problem is modelled as a particular resource leveling problem for which we provide a mixed integer mathematical formulation that we solve with CPLEX. The model allows to evaluate and analyse different scenarios that could be considered by the company in place of the current one in order to rearrange the available human resources used in refueling activity. Experimental results on a set of real test cases provided by an oil & gas company are discussed.

关键词： Ground Aircraft Refueling Resource Leveling Problem mixed integer programming

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Determining production capacity planning in the stochastic demand environment for the food processing manufacturers: A case study

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JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES 2021年第5期42卷 909-936页

作者： Chen, Ping-Shun Tseng, Fang-Yi Chen, Jimmy Ching-Ming Chung Yuan Christian Univ Dept Ind & Syst Engn Taoyuan 320314 Taiwan Wayne State Univ Div Engn Technol Detroit MI 48202 USA

This research studies production scheduling problems with stochastic customer demand for food processing factories to determine a multi-period production schedule that minimizes the total cost and achieves a predetermined customer service level. Based on the practical food processing conditions, this study constructs a mixed integer programming (MIP) mathematical model and applies chance constrained programming (CCP) to transform probabilistic constraints of customer demand into deterministic constraints of customer demand with the associated normal distributions. Using the numerical data, this research verifies the proposed methodology. For sensitivity analysis, the results show that increasing overtime hours decreases the total cost and enhancing customer service level increases the total cost. Furthermore, this study investigates the impacts of different forecasting and production schedules on out-of-stock costs, inventory costs, and both.

关键词： Stochastic demand Production capacity planning Food processing Chance constrained programming mixed integer programming

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Factor Model Based Clustering Approach for Cardinality Constrained Portfolio Selection

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IFAC Proceedings Volumes 2014年第3期47卷 10713-10718页

作者： Kening Jiang Duan Li Jianjun Gao Jeffrey Xu YU Valuation Advisory Services Deloitte & Touche Financial Advisory Services Limited Hong Kong Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai China

Portfolio selection concerns identifying an optimal composition of various risky assets and their corresponding holding amounts such that the corresponding investment strategy strikes a balance between maximizing the expected investment return and minimizing investment risk. While market frictions make full diversification impractical, cardinality constrained mean-variance (CCMV) portfolio selection problem emerges as a natural remedy: Given an asset pool with total n assets and a given cardinality s < n , optimally choose s assets from the entire asset pool such as to achieve a mean-variance efficiency. Unfortunately, CCMV has been proved to be NP hard and has been posted in front of optimization society as a long-standing challenge. By invoking structural market information and utilizing fast clustering algorithm for classification, we develop in this paper an effective heuristic scheme to identify approximate solutions for large-scale CCMV problems. More specifically, by constructing grouping constraints generated from factor-model based clustering algorithm and attaching them to the mixed integer programming formulation associated with the CCMV problem, we are able to significantly reduce the computational complexity, thus offering a fast algorithm with relatively high quality solution.

关键词： Financial optimization portfolio selection mean-variance formulation clustering algorithm factor model mixed integer programming

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